AI Engineer (Azure)

Location: USA

Company

hirify.global provides strategic consulting, program management, and data-driven analytics for federal public health agencies, delivering secure technology solutions and public health initiatives.

What you will do

• Build, enhance, and support production generative AI web applications, including retrieval-based knowledge assistants, chatbots, and agent workflows.
• Develop Python backend services and integrate Azure OpenAI, Azure AI Foundry, Azure AI Search, databases, APIs, enterprise data, cloud services, and MCP-based tools.
• Implement RAG pipelines covering document processing, chunking, embeddings, search, context preparation, and source citations.
• Implement agent workflows with tool and function calling, structured outputs, conversation context, error handling, execution limits, and human review where needed.
• Evaluate retrieval relevance, answer correctness, grounding, reliability, latency, and cost; add logging, tracing, and metrics for production monitoring.
• Troubleshoot defects, support deployments, participate in code reviews, document implementation decisions, and collaborate with AI engineering, architecture, product, data engineering, and DevSecOps teams.

Requirements

• 3+ years of technical experience, including developing and supporting production software applications.
• 1+ year of hands-on generative AI development, including RAG-based assistants or chatbots.
• Python backend development experience with asynchronous APIs using FastAPI, Pydantic, or comparable tools.
• Experience with Git, code reviews, automated testing, CI/CD, and Agile delivery.
• Azure experience, including Azure OpenAI, Azure AI Search, and integration with databases and external services.
• Agent workflow experience with tool calling, structured outputs, and context management using PydanticAI, Microsoft Agent Framework, LangGraph, Foundry Agent Service, or similar tools.
• Ability to conduct LLM evaluation and troubleshooting with test datasets, logs, and traces to assess quality, latency, and cost.
• Hands-on RAG experience with document processing, chunking, embeddings, vector or hybrid search, and citations.
• Bachelor's degree in computer science, engineering, or a related field.
• Must be a US citizen and able to obtain a US Government security clearance, Public Trust 5, within a reasonable period.

Nice to have

• Experience with Langfuse, Pydantic Logfire, similar AI observability tools, and OpenTelemetry.
• Experience with advanced RAG, multi-agent workflows, or MCP integrations.
• Experience with Docker, Azure deployment services, or frontend development using React, Angular, or TypeScript.
• Knowledge of open-source LLM hosting with vLLM, SGLang, or similar frameworks.
• Knowledge of LLM fine-tuning and optimization, including PEFT, LoRA/QLoRA, and quantization.

Culture & Benefits

• Full-time employment with comprehensive medical, dental, vision, and life insurance.
• Paid time off and a 401(k) with company match.
• Growth and promotion opportunities.
• Market-competitive salary commensurate with experience and education.
• Equal opportunity employer, including veterans and people with disabilities.

Hiring process

• Interview responses must be based on the candidate's own knowledge, skills, and experience.
• Use of AI tools or other third-party resources to generate or assist with interview responses is not permitted and may result in disqualification.